Simple and fast MySQL to Elasticsearch sync tool, written in Python.

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This tool helps you to initialize MySQL dump table to Elasticsearch by parsing mysqldump, then incremental sync MySQL table to Elasticsearch by processing MySQL Binlog. Also, during the binlog syncing, this tool will save the binlog sync position, so that it is easy to recover after this tool being shutdown for any reason.

By following these steps.

This tool depends on python lxml package, so that you should install the lxml's dependecies correctly, the libxml2 and libxslt are required.

For example, in CentOS:

sudo yum install libxml2 libxml2-devel libxslt libxslt-devel

Or in Debian/Ubuntu:

sudo apt-get install libxml2-dev libxslt-dev python-dev

See lxml Installation for more infomation.

And then, mysqldump is required in the machine where this tool will be run on it.(and the mysql server must enable binlog)

Then install this tool

pip install py-mysql-elasticsearch-sync

There is a sample config file in repo, you can start by editing it.

Simply run command

es-sync path/to/your/config.yaml

and the tool will dump your data as stream to sync, when dump is over, it will start to sync binlog.

The latest synced binlog file and position are recorded in your info file which is configured in your config file. You can restart dump step by remove it, or you can change sync position by edit it.

Or if you but want to load it from your own dumpfile. You should dump your table first as xml format(by adding -Xoption to your mysqldump command)

then

es-sync path/to/your/config.yaml --fromfile

to start sync, when xml sync is over, it will also start binlog sync.

We provide an upstart script to help you deploy this tool, you can edit it for your own condition, besides, you can deploy it in your own way.

Now Multi-table is supported through setting tables in config file, the first table is master as default and the others are slave.

Master table and slave tables must use the same primary key, which is defined via _id.

Table has higher priority than tables.

• MultiIndex Supporting